The integrated process planning and scheduling problem is a key aspect in manufacturing systems. This paper investigates the integrated process planning and scheduling integration problem based on nonlinear process planning. The study adopts particle swarm optimization algorithm, designs a new flexible scheduling method based on “cursor”, and uses the particle coding method integrated with the process to realize the simultaneous optimization of the integrated process planning route and scheduling. The experimental results of the algorithm show that, compared with the genetic algorithm, the proposed particle swarm optimization algorithm completes the convergence of the two objective functions of completion time and makespan in 59 and 55 iterations, respectively, with the convergence values of 355.32 s and 620.75. In the tests of 10 problems of different sizes, the average value of the IGD of this paper’s algorithm is always within 300, which proves that the nondominated frontier obtained by it is closer to the true frontier. The rescheduling experiments under dynamic events show that the Best makespan results sought by the particle swarm algorithm are reduced by 2.32%-10.26% and the average makespan is reduced by 4.40%-10.38% compared with that of the genetic algorithm. It is shown that the integrated process planning and scheduling integration method based on particle swarm optimization proposed in this paper has better convergence in solving the two sub-problems of process route planning and batch scheduling sequencing, and is able to optimize the production process of the plant more effectively.
